Phase and Defect Engineering of MoSe2 Nanosheets for Enhanced NIR-II Photothermal Immunotherapy.

Inducing immunogenic cell death (ICD) during photothermal therapy (PTT) has the potential to effectively trigger photothermal immunotherapy (PTI). However, ICD induced by PTT alone is often limited by inefficient PTT, low immunogenicity of tumor cells, and a dysregulated redox microenvironment. Herein, we develop MoSe2 nanosheets with high-percentage metallic 1T phase and rich exposed active Mo centers through phase and defect engineering of MoSe2 as an effective nanoagent for PTI. The metallic 1T phase in MoSe2 nanosheets endows them with strong PTT performance, and the abundant exposed active Mo centers endow them with high activity for glutathione (GSH) depletion. The MoSe2-mediated high-performance PTT synergizing with efficient GSH depletion facilitates the release of tumor-associated antigens to induce robust ICD, thus significantly enhancing checkpoint blockade immunotherapy and activating systemic immune response in mouse models of colorectal cancer and triple-negative metastatic breast cancer.

Boosting Bifunctional Catalysis by Integrating Active Faceted Intermetallic Nanocrystals and Strained Pt-Ir Functional Shells.

PtIr-based nanostructures are fascinating materials for application in bifunctional oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) catalysis. However, the fabrication of PtIr nanocatalysts with clear geometric features and structural configurations, which are crucial for enhancing the bifunctionality, remains challenging. Herein, PtCo@PtIr nanoparticles are precisely designed and fabricated with a quasi-octahedral PtCo nanocrystal as a highly atomically ordered core and an ultrathin PtIr atomic layer as a compressively strained shell. Owing to their geometric and core-shell features, the PtCo@PtIr nanoparticles deliver approximately six and eight times higher mass and specific activities, respectively, as an ORR catalyst than a commercial Pt/C catalyst. The half-wave potential of PtCo@PtIr exhibits a negligible decrease by 9 mV after 10 000 cycles, indicating extraordinary ORR durability because of the ordered arrangement of Pt and Co atoms. When evaluated using the ORR-OER dual reaction upon the introduction of Ir, PtCo@PtIr exhibits a small ORR-OER overpotential gap of 679 mV, demonstrating its great potential as a bifunctional electrocatalyst for fabricating fuel cells. The findings pave the way for designing precise intermetallic core-shell nanocrystals as highly functional catalysts.

Reduction of Oxidative Stress and Excitotoxicity by Mesenchymal Stem Cell Biomimetic Co-Delivery System for Cerebral Ischemia-Reperfusion Injury Treatment.

A cerebral ischemia-reperfusion injury is ensued by an intricate interplay between various pathological processes including excitotoxicity, oxidative stress, inflammation, and apoptosis. For a long time, drug intervention policies targeting a single signaling pathway have failed to achieve the anticipated clinical efficacy in the intricate and dynamic inflammatory environment of the brain. Moreover, inadequate targeted drug delivery remains a significant challenge in cerebral ischemia-reperfusion injury therapy. In this study, a multifunctional nanoplatform (designated as PB-006@MSC) is developed using ZL006-loaded Prussian blue nanoparticles (PBNPs) camouflaged by a mesenchymal stem cell (MSC) membrane (MSCm). ZL006 is a neuroprotectant. It can be loaded efficiently into the free radical scavenger PBNP through mesoporous adsorption. This can simultaneously modulate multiple targets and pathways. MSCm biomimetics can reduce the nanoparticle immunogenicity, efficiently enhance their homing capability to the cerebral ischemic penumbra, and realize active-targeting therapy for ischemic stroke. In animal experiments, PB-006@MSC integrated reactive oxygen species (ROS) scavenging and neuroprotection. Thereby, it selectively targeted the cerebral ischemic penumbra (about fourfold higher accumulation at 24 h than in the non-targeted group), demonstrated a remarkable therapeutic efficacy in reducing the volume of cerebral infarction (from 37.1% to 2.3%), protected the neurogenic functions, and ameliorated the mortality.

Detection of transcription factors binding to methylated DNA by deep recurrent neural network.

Transcription factors (TFs) are proteins specifically involved in gene expression regulation. It is generally accepted in epigenetics that methylated nucleotides could prevent the TFs from binding to DNA fragments. However, recent studies have confirmed that some TFs have capability to interact with methylated DNA fragments to further regulate gene expression. Although biochemical experiments could recognize TFs binding to methylated DNA sequences, these wet experimental methods are time-consuming and expensive. Machine learning methods provide a good choice for quickly identifying these TFs without experimental materials. Thus, this study aims to design a robust predictor to detect methylated DNA-bound TFs. We firstly proposed using tripeptide word vector feature to formulate protein samples. Subsequently, based on recurrent neural network with long short-term memory, a two-step computational model was designed. The first step predictor was utilized to discriminate transcription factors from non-transcription factors. Once proteins were predicted as TFs, the second step predictor was employed to judge whether the TFs can bind to methylated DNA. Through the independent dataset test, the accuracies of the first step and the second step are 86.63% and 73.59%, respectively. In addition, the statistical analysis of the distribution of tripeptides in training samples showed that the position and number of some tripeptides in the sequence could affect the binding of TFs to methylated DNA. Finally, on the basis of our model, a free web server was established based on the proposed model, which can be available at https://bioinfor.nefu.edu.cn/TFPM/.

Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma.

OBJECTIVE: To investigate the value of differential diagnosis of hepatocellular carcinoma (HCC) and non-hepatocellular carcinoma (non-HCC) based on CT and MR multiphase radiomics combined with different machine learning models and compare the diagnostic efficacy between different radiomics models. BACKGROUND: Primary liver cancer is one of the most common clinical malignancies, hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, accounting for approximately 90% of cases. A clear diagnosis of HCC is important for the individualized treatment of patients with HCC. However, more sophisticated diagnostic modalities need to be explored. METHODS: This retrospective study included 211 patients with liver lesions: 97 HCC and 124 non-hepatocellular carcinoma (non-HCC) who underwent CT and MRI. Imaging data were used to obtain imaging features of lesions and radiomics regions of interest (ROI). The extracted imaging features were combined to construct different radiomics models. The clinical data and imaging features were then combined with radiomics features to construct the combined models. Support Vector Machine (SVM), K-nearest Neighbor (KNN), RandomForest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Multilayer Perceptron (MLP) six machine learning models were used for training. Five-fold cross-validation was used to train the models, and ROC curves were used to analyze the diagnostic efficacy of each model and calculate the accuracy rate. Model training and efficacy test were performed as before. RESULTS: Statistical analysis showed that some clinical data (gender and concomitant cirrhosis) and imaging features (presence of envelope, marked enhancement in the arterial phase, rapid contouring in the portal phase, uniform density/signal and concomitant steatosis) were statistical differences (P < 0.001). The results of machine learning models showed that KNN had the best diagnostic efficacy. The results of the combined model showed that SVM had the best diagnostic efficacy, indicating that the combined model (accuracy 0.824) had better diagnostic efficacy than the radiomics-only model. CONCLUSIONS: Our results demonstrate that the radiomic features of CT and MRI combined with machine learning models enable differential diagnosis of HCC and non-HCC (malignant, benign). The diagnostic model with dual radiomic had better diagnostic efficacy. The combined model was superior to the radiomic model alone.

Exploring and clinical validation of prognostic significance and therapeutic implications of copper homeostasis-related gene dysregulation in acute myeloid leukemia.

The patterns and biological functions of copper homeostasis-related genes (CHRGs) in acute myeloid leukemia (AML) remain unclear. We explored the patterns and biological functions of CHRGs in AML. Using independent cohorts, including TCGA-GTEx, GSE114868, GSE37642, and clinical samples, we identified 826 common differentially expressed genes. Specifically, 12 cuproptosis-related genes (e.g., ATP7A, ATP7B) were upregulated, while 17 cuproplasia-associated genes (e.g., ATOX1, ATP7A) were downregulated in AML. We used LASSO-Cox, Kaplan-Meier, and Nomogram analyses to establish prognostic risk models, effectively stratifying patients with AML into high- and low-risk groups. Subgroup analysis revealed that high-risk patients exhibited poorer overall survival and involvement in fatty acid metabolism, apoptosis, and glycolysis. Immune infiltration analysis indicated differences in immune cell composition, with notable increases in B cells, cytotoxic T cells, and memory T cells in the low-risk group, and increased monocytes and neutrophils in the high-risk group. Single-cell sequencing analysis corroborated the expression characteristics of critical CHRGs, such as MAPK1 and ATOX1, associated with the function of T, B, and NK cells. Drug sensitivity analysis suggested potential therapeutic agents targeting copper homeostasis, including Bicalutamide and Sorafenib. PCR validation confirmed the differential expression of 4 cuproptosis-related genes (LIPT1, SLC31A1, GCSH, and PDHA1) and 9 cuproplasia-associated genes (ATOX1, CCS, CP, MAPK1, SOD1, COA6, PDK1, DBH, and PDE3B) in AML cell line. Importantly, these genes serve as potential biomarkers for patient stratification and treatment. In conclusion, we shed light on the expression patterns and biological functions of CHRGs in AML. The developed risk models provided prognostic implications for patient survival, offering valuable information on the regulatory characteristics of CHRGs and potential avenues for personalized treatment in AML.

Discovery and development of novel 10,12-disubstituted aloperine derivatives against HCoV-OC43 by targeting allosteric site of host TMPRSS2.

By inducing steric activation of the 10CH bond with a 12-acyl group to form a key imine oxime intermediate, 20 novel (10S)-10,12-disubstituted aloperine derivatives were successfully synthesized and assessed for their antiviral efficacy against HCoV-OC43. Of them, compound 3i exhibited the moderate activities against HCoV-OC43, as well as against the SARS-CoV-2 variant EG.5.1 with the comparable EC50 values of 4.7 and 4.1 µM. A mechanism study revealed that it inhibited the protease activity of host TMPRSS2 by binding to an allosteric site, rather than the known catalytic center, different from that of camostat. Also, the combination of compound 3i and molnupiravir, as an RdRp inhibitor, showed an additive antiviral effect against HCoV-OC43. The results provide a new binding mode and lead compound for targeting TMPRSS2, with an advantage in combating broad-spectrum coronavirus.

Determination of carboxylesterase by fluorescence probe to guide detection of carbamate pesticide.

A carboxylesterase fluorescent probe (Probe 1) was developed for determination of carboxylesterase to guide detection of carbamate pesticide. The probe uses benzothiazole as fluorescence group and phenyldimethyl carbamate as recognition group. The solution of the fluorescent probe gradually changes from light blue to dark blue as the concentration of carbamate pesticides increases. The concentration of carbamate pesticides can be quickly calculated according to the colour of the probe solution through Get Color software on a smartphone. It showed that Probe 1 can be used as a rapid detection tool to achieve rapid detection of carbamate pesticides in juice samples without professional personnel and equipment. Furthermore, the probe has been successfully used to detect carbamate pesticides in fruit juice and vegetable juice.

Upregulation of Hepatic Glutathione S-Transferase Alpha 1 Ameliorates Metabolic Dysfunction-Associated Steatosis by Degrading Fatty Acid Binding Protein 1.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common metabolic disease of the liver, characterized by hepatic steatosis in more than 5% of hepatocytes. However, despite the recent approval of the first drug, resmetirom, for the management of metabolic dysfunction-associated steatohepatitis, decades of target exploration and hundreds of clinical trials have failed, highlighting the urgent need to find new druggable targets for the discovery of innovative drug candidates against MASLD. Here, we found that glutathione S-transferase alpha 1 (GSTA1) expression was negatively associated with lipid droplet accumulation in vitro and in vivo. Overexpression of GSTA1 significantly attenuated oleic acid-induced steatosis in hepatocytes or high-fat diet-induced steatosis in the mouse liver. The hepatoprotective and anti-inflammatory drug bicyclol also attenuated steatosis by upregulating GSTA1 expression. A detailed mechanism showed that GSTA1 directly interacts with fatty acid binding protein 1 (FABP1) and facilitates the degradation of FABP1, thereby inhibiting intracellular triglyceride synthesis by impeding the uptake and transportation of free fatty acids. Conclusion: GSTA1 may be a good target for the discovery of innovative drug candidates as GSTA1 stabilizers or enhancers against MASLD.

Highly Stable Carboranyl Ligated Gold Nano-catalysts for Regioselective Aromatic Bromination.

Achieving electronic/steric control and realizing selectivity regulation in nanocatalysis remains a formidable challenge, as the dynamic nature of metal-ligand interfaces, including dissolution (metal leaching) and structural reconstruction, poses significant obstacles. Herein, we disclose carboranyls (CBs) as unprecedented carbon-bonded functional ligands (Eads.CB-Au(111) = -2.90 eV) for gold nanoparticles (AuNPs), showcasing their exceptional stabilization capability that is attributed by strong Au-C bonds combined with B-H⋯Au interactions. The synthesized CB@AuNPs exhibit core(Aun)-satellite(CB2Au-) structure, showing high stability towards multiple stimuli (110oC, pH = 1-12, thiol etchants). In addition, different from conventional AuNP catalysts such as triphenylphosphine (PPh3) stabilized AuNPs, dissolution of catalytically active gold species was suppressed in CB@AuNPs under the reaction conditions. Leveraging these distinct features, CB@AuNPs realized outstanding p:o selectivities in aromatic bromination. Unbiased arenes including chlorobenzene (up to > 30:1), bromobenzene (15:1) and phenyl acrylate were examined using CB@AuNPs as catalysts to afford highly-selective p-products. Both carboranyl ligands and carboranyl derived counterions are crucial for such regioselective transformation. This work has provided valuable insights for AuNPs in realizing diverse regioselective transformations.

In vivo CRISPR screens identify RhoV as a pro-metastasis factor of triple-negative breast cancer.

Metastasis is the main death reason for triple-negative breast cancer (TNBC). Thus, identifying the driver genes associated with metastasis of TNBC is urgently needed. CRISPR screens have dramatically enhanced genome editing and made it possible to identify genes associated with metastasis. In this study, we identified and explored the crucial role of ras homolog family member V (RhoV) in TNBC metastasis. Here, we performed customized in vivo CRISPR screens targeting metastasis-related genes obtained from transcriptome analysis of TNBC. The regulatory role of RhoV in TNBC was validated using gain- or loss-of-function studies in vitro and in vivo. We further conducted immunoprecipitation and LC-MS/MS to explore the metastasis mechanism of RhoV. In vivo functional screens identified RhoV as a candidate regulator involved in tumor metastasis. RhoV was frequently upregulated in TNBC and correlated with poor survival. Knockdown of RhoV significantly suppressed cell invasion, migration, and metastasis both in vitro and in vivo. In addition, we provided evidence that p-EGFR interacted with RhoV to activate the downstream signal pathway of RhoV, thereby promoting tumor metastasis. We further confirmed that this association was dependent on GRB2 through a specific proline-rich motif in the N-terminus of RhoV. This mechanism of RhoV is unique, as other Rho family proteins lack the proline-rich motif in the N-terminus.

All HER2-negative breast cancer patients need gBRCA testing: cost-effectiveness and clinical benefits.

BACKGROUND: The OlympiA trial demonstrated the benefits of adjuvant usage of olaparib for high-risk patients with human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) and germline BRCA (gBRCA) mutation. This provoked thoughts on the clinical criteria of gBRCA testing. This study aims to estimate the costs and benefits of gBRCA testing and adjuvant olaparib therapy for patients with triple-negative breast cancer (TNBC) and hormone-receptor (HR)-positive and HER2-negative BC in China and the United States of America (USA). METHODS: We used a Markov chain decision tree analytic model to compare three gBRCA screening policies in China and the USA: (1) no gBRCA testing; (2) selected gBRCA testing and (3) universal gBRCA testing for nonmetastatic TNBC and HR-positive HER2-negative BC patients. We modelled the benefit of systemic therapy and risk-reducing surgeries among patients identified with pathogenic or likely pathogenic variants (PVs) in BRCA1 and BRCA2. RESULTS: Changing from the selected gBRCA testing to the universal gBRCA testing in TNBC patients is cost-effective, with the incremental cost-effectiveness ratios (ICERs) being 10991.1 and 56518.2 USD/QALY in China and the USA, respectively. Expanding universal gBRCA testing to HR-positive HER2-negative BC and TNBC patients has ICERs of 2023.3 and 16611.1 USD/QALY in China and the USA, respectively. DISCUSSION: By performing gBRCA testing on all HER2-negative BC patients, adjuvant olaparib can be offered to high-risk patients with a PV in BRCA1 or BRCA2. These patients are also candidates for risk-reducing surgeries, an important aspect of their survivorship care, and these interventions can improve survival outcomes. With the willingness-to-pay thresholds being 31,500.0 and 100,000.0 USD per QALY gained in China and the USA, respectively, universal gBRCA testing is likely cost-effective for all HER2-negative BC patients. This simplified criterion of gBRCA testing for BC is recommended for adoption by current guidelines in China and the USA.

Complete genome analysis of echovirus 30 strains isolated from hand-foot-and-mouth disease in Yunnan province, China.

BACKGROUND: Echovirus 30 is prone to cause hand-foot-and-mouth disease in infants and children. However, molecular epidemiologic information on the spread of E30 in southwestern China remains limited. In this study, we determined and analyzed the whole genomic sequences of E30 strains isolated from the stools of patients with hand-foot-and-mouth disease in Yunnan Province, China, in 2019. METHODS: E30 isolates were obtained from fecal samples of HFMD patients. The whole genomes were sequenced by segmented PCR and analyzed for phylogeny, mutation and recombination. MEGA and DNAStar were used to align the present isolates with the reference strains. The VP1 sequence of the isolates were analyzed for selection pressure using datamonkey server. RESULTS: The complete genome sequences of four E30 were obtained from this virus isolation. Significant homologous recombination signals in the P2-3'UTR region were found in all four isolates with other serotypes. Phylogenetic analysis showed that the four E30 isolates belonged to lineage H. Comparison of the VP1 sequences of these four isolates with other E30 reference strains using three selection pressure analysis models FUBAR, FEL, and MEME, revealed a positive selection site at 133rd position. CONCLUSIONS: This study extends the whole genome sequence of E30 in GenBank, in which mutations and recombinations have driven the evolution of E30 and further improved and enriched the genetic characteristics of E30, providing fundamental data for the prevention and control of diseases caused by E30. Furthermore, we demonstrated the value of continuous and extensive surveillance of enterovirus serotypes other than the major HFMD-causing viruses.

Identification of T Cell Epitopes in the Spike Glycoprotein of Severe Acute Respiratory Syndrome Coronavirus 2 in Rhesus Macaques.

The T cell response is an important detection index in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine development. The present study was undertaken to determine the T cell epitopes in the spike (S) protein of SARS-CoV-2 that dominate the T cell responses in SARS-CoV-2-infected patients. PBMCs from rhesus macaques vaccinated with a DNA vaccine encoding the full-length S protein were isolated, and an ELISPOT assay was used to identify the recognized T cell epitopes among a total of 158 18-mer and 10-aa-overlapping peptides spanning the full-length S protein. Six multipeptide-based epitopes located in the S1 region, with four of the six located in the receptor-binding domain, were defined as the most frequently recognized epitopes in macaques. The conservation of the epitopes across species was also verified, and peptide mixtures for T cell response detection were established. Six newly defined T cell epitopes were found in the current study, which may provide a novel potential target for T cell response detection and the diagnosis and vaccine design of SARS-CoV-2 based on multipeptide subunit-based epitopes.

Advances in air pollution control for vessels in China.

Vessel emissions have contributed a great deal to air quality deterioration in China. Hence, the Chinese government has promulgated a series of stringent emission regulations. It is in this context that vessel emission control technology research is in full swing. In particular, during the 13th Five-Year Plan, the air pollution control technology of vessels has greatly improved. Vessel emission control has followed two main governance routes: source emission reduction and aftertreatment technology. Source control focuses on alternative fuels, with two main directions, the development of new fuels and the modification of existing fuels. Moreover, after-treatment technologies have also been developed, including wet desulfurization technology using seawater or alkaline liquids as wet washing liquids and selective catalytic reduction (SCR) for the control of NOx emission. Due to China's increasingly stringent emissions standards and regulations, work on the development of clean alternative fuels and further upgrading the collaborative application of after-treatment technologies to meet the near-zero-emissions requirements of vessels is still necessary.

Advances in air pollution control for key industries in China during the 13th five-year plan.

Industrial development is an essential foundation of the national economy, but the industry is also the largest source of air pollution, of which power plants, iron and steel, building materials, and other industries emit large amounts of pollutants. Therefore, the Chinese government has promulgated a series of stringent emission regulations, and it is against this backdrop that research into air pollution control technologies for key industrial sectors is in full swing. In particular, during the 13th Five-Year Plan, breakthroughs have been made in pollution control technology for key industrial sectors. A multi-pollutant treatment technology system of desulfurization, denitrification, and dust collection, which applies to key industries such as power plants, steel, and building materials, has been developed. High-performance materials for the treatment of different pollutants, such as denitrification catalysts and desulfurization absorbers, were developed. At the same time, multi-pollutant synergistic removal technologies for flue gas in various industries have also become a hot research topic, with important breakthroughs in the synergistic removal of NOx, SOx, and Hg. Due to the increasingly stringent emission standards and regulations in China, there is still a need to work on the development of multi-pollutant synergistic technologies and further research and development of synergistic abatement technologies for CO2 to meet the requirements of ultra-low emissions in industrial sectors.

The neural mechanisms underlying the modulation of attentional deployment on emotional stability.

Emotional stability, the change of emotion response among situations, was associated with mental illness, such as depression. The current study aimed to explore the modulation of attentional deployment on emotional stability by combining functional magnetic resonance imaging (fMRI) and a sequential risk-taking task. During the task, participants were asked to open a series of boxes consecutively and decided when to stop. Each box contained a reward, except one containing a devil to zero reward in the trial. When participants stopped, both collected gains and missed chances were revealed. The attentional deployment was manipulated during the outcome feedback, i.e., inducing participants to focus on the good part (GF context) or the bad part (MF context) of the decision outcome. Besides, the Control context was also set, in which the attentional deployment was not manipulated. The behavioral results showed that the emotional stability was stronger in GF context relative to MF and Control contexts. At the neural level, with outcomes getting better, activations of ventral striatum (VS) and superior frontal gyrus (SFG) increased faster in GF context than that in MF and Control contexts. In addition, in GF context, the changing of SFG activation with outcomes getting better was associated with emotional stability. The current study highlighted that focusing on the good part of decision outcomes could enhance emotional stability effectively and SFG played a vital role in this process.

Probing interfacial charge transfer in heterojunctions for photocatalysis.

Photocatalytic reactions can sustainably utilize inexhaustible solar energy for environmental remediation and conversion of photon energy into chemical energy, and thereby show great potential in alleviating the environmental stress and energy crisis. In particular, the constructed heterojunction photocatalysts, typically represented by type II and direct Z-scheme systems, possess many advantages, including broad light spectrum harvesting, decreased recombination rate of photogenerated electron-hole pairs and spatially separated photoreaction active sites, which are critical for enhancing the photocatalytic performance. However, the two systems are often indistinguishable because of the similar band structures. This perspective summarizes the state-of-the-art characterization methods that have been used to precisely probe interfacial charge transfer in the heterojunctions for photocatalysis, including those for the investigation of surface reactions, surface photovoltage, free radical trapping, binding energy shift and photogenerated charge carrier dynamics, as well as theoretical calculations. Based on these results, type II and direct Z-scheme charge transfer mechanisms can be distinguished. The future challenges and prospects in developing such characterization techniques are also discussed.

Bulk and single-cell transcriptome profiling reveal the metabolic heterogeneity in human breast cancers.

An emerging view regarding cancer metabolism is that it is heterogeneous and context-specific, but it remains to be elucidated in breast cancers. In this study, we characterized the energy-related metabolic features of breast cancers through integrative analyses of multiple datasets with genomics, transcriptomics, metabolomics, and single-cell transcriptome profiling. Energy-related metabolic signatures were used to stratify breast tumors into two prognostic clusters: cluster 1 exhibits high glycolytic activity and decreased survival rate, and the signatures of cluster 2 are enriched in fatty acid oxidation and glutaminolysis. The intertumoral metabolic heterogeneity was reflected by the clustering among three independent large cohorts, and the complexity was further verified at the metabolite level. In addition, we found that the metabolic status of malignant cells rather than that of nonmalignant cells is the major contributor at the single-cell resolution, and its interactions with factors derived from the tumor microenvironment are unanticipated. Notably, among various immune cells and their clusters with distinguishable metabolic features, those with immunosuppressive function presented higher metabolic activities. Collectively, we uncovered the heterogeneity in energy metabolism using a classifier with prognostic and therapeutic value. Single-cell transcriptome profiling provided novel metabolic insights that could ultimately tailor therapeutic strategies based on patient- or cell type-specific cancer metabolism.

Altered neural responses to missed chance contribute to the risk-taking behaviour in individuals with Internet gaming disorder.

Missed chance is a powerful factor in shaping risk-taking behaviour. The abnormal risk-taking behaviour is an obvious feature of individuals with Internet gaming disorder (IGD). However, the relationship between the neural responses to missed chance and risk-taking behaviour in IGD individuals remains unclear. In the current fMRI study, 28 IGD subjects (12 female, 23.04 ± 2.43 years old) and 26 healthy control (HC) subjects (13 female, 23.58 ± 2.67 years old) participated in fMRI scanning during performance of a sequential risk-taking task. The general linear model and the psycho-physiological interaction analyses were conducted to explore the difference in neural responses between the two groups. The results showed that IGD subjects reported more regret for the large missed chance and took more risk than HC subjects. Moreover, compared with HC subjects, IGD subjects exhibited greater activations in brain regions like ventral striatum (VS) and superior frontal gyrus (SFG), and stronger VS-thalamus functional connectivity for the large missed chance. Additionally, among IGD subjects, the SFG activation for the large missed chance was positively correlated with the risk-taking behaviour. Together, the results revealed the altered neural responses to missed chance contributed to the risk-taking behaviour in IGD individuals. The findings could help to clearly understand why IGD individuals continue playing online games despite the risks of widely known and could provide a new perspective for the intervention of IGD.